Productivity Claude Skills
3 457 productivity skills from 510 authors. They keep notes, tasks, calendars and plans in order. Half of them fit into 1 851 tokens or less — that is what one costs your context window when the agent loads it. 479 ship runnable scripts rather than instructions alone. 51 of them cannot work without an MCP server, most often rube. We also found 364 copies of these same skills sitting in other people's repositories — counted once here, not 364 times.
3 457 unique 510 authors 6 updated this month 293 from vendors
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Invoke this skill when performing travel planning. It defines a structured workflow for generating itineraries. Following this workflow is essential to ensure the final plan satisfies user requirements.
Schedule recurring agent tasks using cron expressions. Use when the user asks to run something on a schedule, check something periodically, automate a recurring task, set up a cron job, or wants work to happen while they're away. Trigger words: schedule, recurring, cron, every hour, every day, run daily, periodic, automated.
Iteratively review an instar-development spec with multi-angle internal reviewers (security, scalability, adversarial, integration, decision-completeness, lessons-aware) and real cross-model external reviewers routed through the agent's own installed CLIs (codex → GPT-tier, gemini → Gemini-tier; one pass per available family) until convergence, then produce a comprehensive ELI10 convergence report. Output is a spec tagged review-convergence — one of the two tags /instar-dev requires before it will touch instar source. NOT user-invocable; run by the instar-developing agent before any spec-driven /instar-dev work.
Guide for working with Vaultr, an AI-native personal note-taking system. Use this skill whenever the user wants to search, find, read, write, save, create, modify, delete, or capture notes — including journal entries, research notes, quick thoughts, knowledge retrieval, or any note-taking task. Trigger when the user says things like 'save this as a note', 'find my notes about X', 'create a note', 'look up my notes on X', 'read my note about Y', 'delete a note', 'quick note', 'short note', 'what do I know about X', or any variation of managing notes in Vaultr.
Convert bounded mailbox and calendar evidence into a reviewable executive action packet.
Produce a decision-ready ecosystem briefing from fresh governed evidence without claiming publication.
Advance one declared incident through a fixed roster, approval-bound communications planning, and receipt-backed resolution while canonical agency owns durable state.
Route a validated lead to direct outreach planning, nurture planning, or a recorded hold, preserving why that path was chosen.
Fetch National Weather Service forecast evidence through the governed HTTP front, producing a sealed provider packet for downstream weather planning.
Build a scoped taste profile packet from examples, preferences, and explicit dislikes so downstream agents can make style decisions without inventing the user's taste.
Normalize supplied provider weather evidence into a provenance-bound forecast packet with uncertainty and stop conditions. Use when a downstream planning workflow needs provider-neutral weather context; do not use it to fetch forecasts, make life-safety decisions, or perform downstream actions.
Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and streaming approaches.
Use when auditing an agent codebase against the 12-Factor Agents methodology, reviewing LLM-powered system architecture, or assessing agentic app compliance. Triggers on \"analyze agent architecture\", \"12-factor audit\", \"how compliant is this agent\", or \"evaluate this LLM app\". Also applies when comparing frameworks or planning agent improvements. Not for quick checklists \u2014 this performs deep per-factor codebase analysis with file-level evidence.
Use when writing or formatting an ADR document using the MADR template, applying Definition of Done (E.C.A.D.R.) criteria, or verifying ADR completeness. Triggers on \"write the ADR\", \"format as MADR\", \"check ADR quality\", \"mark gaps in ADR\". Also triggers when a decision has been extracted and needs to become a document. Does NOT extract decisions from conversations (use adr-decision-extraction) or orchestrate the full extract-confirm-write workflow (use write-adr).
Use when you need to mine a conversation, session transcript, or design discussion for architectural decisions before writing ADRs. Identifies problem-solution pairs, trade-off debates, technology choices, and explicit \"[ADR]\" tags. Triggers on \"what decisions did we make\", \"extract decisions from this chat\", \"find the choices in our discussion\", or \"summarize architectural decisions\". Also useful after long planning sessions to capture decisions that were made implicitly. Does NOT write ADR documents \u2014 use adr-writing or write-adr for that.
Use when the user wants a cited, structured read of local documents and project knowledge. Triggers on: \"analyze these docs\", \"scan my project for context\", \"read the docs folder\", \"summarize what's in .beagle/concepts/\", \"extract context from docs/\", \"what's in this folder\", \"go read everything in X and tell me what's there\". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups (\"find this function\", \"search the repo\"), web research (use web-research), LLM-as-judge evaluation (use llm-judge), or document editing (use humanize-beagle). Produces a written scan plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced claims.
Use when the user wants to pressure-test a product, internal-tool, or OSS concept against Amazon's Working Backwards PRFAQ gauntlet before committing to a spec. Triggers on: \"work backwards\", \"write a PRFAQ\", \"press release first\", \"is this idea worth building\", \"pressure-test this concept\", \"filter this before brainstorm\", \"is this a real product\". Also catches solution-first pitches (\"I want to build X that does Y\") and technology-first pitches (\"use AI to...\") that need customer-first filtering. Produces a binary pass/fail verdict, not a polished doc. Hardcore coaching — direct, skeptical, concrete. On pass, hands off to brainstorm-beagle with a concept brief. Does NOT write code, plan implementation, scaffold projects, or draft specs.
Use when the user has a fuzzy idea and wants to shape it into a concrete project spec before planning or building. Triggers on: \"brainstorm this\", \"I have an idea for...\", \"help me think through this project\", \"what should I build\", \"spec this out\". Also catches vague feature descriptions needing structured questioning to clarify scope. Does NOT write code, plan implementation, review strategy docs, or run strategy interviews \u2014 produces a WHAT/WHY spec through dialogue, not a HOW plan.
Use when the user wants to build or think through a strategy via guided conversation \u2014 for a company, product, team, career, or initiative. Triggers on \"help me figure out our direction\", \"what should we focus on\", strategic planning, competitive positioning, go-to-market strategy. Also catches indirect requests like prioritization struggles or \"we have too many priorities\". Does NOT review existing strategy documents (use strategy-review) or brainstorm project features (use brainstorm-beagle).
Use as the follow-up to brainstorm-beagle when a spec has an Open Questions section (or quietly carries latent gaps) that need closing before planning or implementation can begin. Triggers on: \"resolve the open questions\", \"close the gaps in this spec\", \"research the open items\", \"finalize my spec\", \"make this spec implementation-ready\", \"answer the TBDs\". Also triggers whenever the user points at a brainstorm-beagle spec and asks for research, proposals, or answers to unresolved items. Orchestrates parallel research subagents when available (falls back to inline sequential research otherwise), proposes answers one at a time for user approval, then rewrites the spec in place so it arrives at planning with no known gaps. Does NOT write code, design implementation, or create plans — it only produces a complete spec.
Creates a NEW Architectural Decision Record (ADR) documenting a specific architectural decision. Use when the user requests "Create ADR for [topic]", "Document decision about [topic]", "Write ADR for [choice]", or when documenting technology choices, patterns, or architectural approaches. Do NOT use for reviews (use architecture-review or specialist-review), checking existing ADRs (use architecture-status), or general documentation.
Reports on the health and state of architecture documentation (counts of ADRs, reviews, activity levels, documentation gaps). Use when the user asks "What's our architecture status?", "Show architecture documentation", "How many ADRs do we have?", "What decisions are documented?", "Architecture health check", or wants an overview/summary of documentation state. Do NOT use for listing team members (use list-members), creating new documents (use create-adr), or conducting reviews (use architecture-review or specialist-review).
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool ...
Create a structured implementation plan for a feature or change. This documentation shall serve Agents and Humans. Produces a plan with requirements, phases, implementation steps, todo list, and Definition of Done. Use this skill when the user wants to plan a non-trivial feature before implementing it.
Draws 4 Tarot cards using os.urandom() to inject entropy into planning when prompts are vague or underspecified. Interprets the spread to guide next steps. Use when the user is nonchalant, feeling lucky, says 'let fate decide', makes Yu-Gi-Oh references ('heart of the cards'), demonstrates indifference about approach, or says 'try again' on a system with no changes. Also triggers on sufficiently ambiguous prompts where multiple approaches are equally valid.
Simulate a structured peer-review process using multiple specialized agents to validate designs, surface hidden assumptions, and identify failure modes before implementation.
A micro-prompt that reminds the agent that it is an interactive programmer. Works great in Clojure when Copilot has access to the REPL (probably via Backseat Driver). Will work with any system that has a live REPL that the agent can use. Adapt the prompt with any specific reminders in your workflow and/or workspace.
Structured Autonomy Planning Prompt
Use when tackling complex reasoning tasks requiring step-by-step logic, multi-step arithmetic, commonsense reasoning, symbolic manipulation, or problems where simple prompting fails - provides comprehensive guide to Chain-of-Thought and related prompting techniques (Zero-shot CoT, Self-Consistency, Tree of Thoughts, Least-to-Most, ReAct, PAL, Reflexion) with templates, decision matrices, and research-backed patterns
Update the llms.txt file in the root folder to reflect changes in documentation or specifications following the llms.txt specification at https://llmstxt.org/
Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA.
Automate Box cloud storage operations including file upload/download, search, folder management, sharing, collaborations, and metadata queries via Rube MCP (Composio). Always search tools first for...
Automate Canva tasks via Rube MCP (Composio): designs, exports, folders, brand templates, autofill. Always search tools first for current schemas.
You are a workflow automation expert specializing in creating efficient CI/CD pipelines, GitHub Actions workflows, and automated development processes. Design automation that reduces manual work, i...
Automate ClickUp project management including tasks, spaces, folders, lists, comments, and team operations via Rube MCP (Composio). Always search tools first for current schemas.
Automate Dropbox file management, sharing, search, uploads, downloads, and folder operations via Rube MCP (Composio). Always search tools first for current schemas.
Generate workflow JSON files for chaining AI models
Automate Google Calendar events, scheduling, availability checks, and attendee management via Rube MCP (Composio). Create events, find free slots, manage attendees, and list calendars programmatica...
Automate Google Drive file operations (upload, download, search, share, organize) via Rube MCP (Composio). Upload/download files, manage folders, share with permissions, and search across drives pr...
Automate Google Calendar tasks via Rube MCP (Composio). Always search tools first for current schemas.
Automate Google Meet tasks via Rube MCP (Composio): create Meet spaces, schedule video conferences via Calendar events, manage meeting access. Always search tools first for current schemas.
Automate Jira tasks via Rube MCP (Composio): issues, projects, sprints, boards, comments, users. Always search tools first for current schemas.
Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, or scheduled tasks.
Automate OneDrive file management, search, uploads, downloads, sharing, permissions, and folder operations via Rube MCP (Composio). Always search tools first for current schemas.
Automate Outlook tasks via Rube MCP (Composio): emails, calendar, contacts, folders, attachments. Always search tools first for current schemas.
Automate Outlook Calendar tasks via Rube MCP (Composio): create events, manage attendees, find meeting times, and handle invitations. Always search tools first for current schemas.